Generalized Linear Model
#gdp_rightsbased$SpeciesCat <- factor(gdp_rightsbased$SpeciesCat)
itq_glm <- glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial", data = gdp_rightsbased)
itq_glm
##
## Call: glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial",
## data = gdp_rightsbased)
##
## Coefficients:
## (Intercept) current_gdp SpeciesCat
## -1.435e+00 9.518e-05 -9.519e-02
##
## Degrees of Freedom: 289 Total (i.e. Null); 287 Residual
## Null Deviance: 320.5
## Residual Deviance: 195.5 AIC: 201.5
summary(itq_glm)
##
## Call:
## glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial",
## data = gdp_rightsbased)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.08034 -0.51602 -0.15462 -0.02795 2.71930
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.435e+00 1.151e+00 -1.247 0.212
## current_gdp 9.518e-05 1.562e-05 6.095 1.10e-09 ***
## SpeciesCat -9.519e-02 2.335e-02 -4.076 4.58e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 320.55 on 289 degrees of freedom
## Residual deviance: 195.45 on 287 degrees of freedom
## AIC: 201.45
##
## Number of Fisher Scoring iterations: 6
F/Fmsy vs. B/Bmsy for all fisheries